Construction duration predictive model based on factorial analysis and fuzzy logic
Auteur(s): |
Luiz Maurício Furtado Maués
José Alberto Silva de Sá Carlos Tavares da Costa Junior Andrea Parise Kern André Augusto Azevedo Montenegro Duarte |
---|---|
Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Ambiente Construído, décembre 2019, n. 4, v. 19 |
Page(s): | 115-133 |
DOI: | 10.1590/s1678-86212019000400346 |
Abstrait: |
Setting the building construction duration for vertical residential works is made still in the study phase of economic and financial feasibility of the project and, in most cases, in an empirical way, increasing the uncertainties and the risks to fulfill the set deadline. However, there are computational intelligence tools that can contribute to reduce the degree of uncertainty. This study aimed to investigate the use of a hybrid system to estimate the deadline for vertical residential building works from design and production characteristics using factorial analysis and Fuzzy Systems. To this end, we used information of a database from the SEURB and in some buildings construction companies in Belém, a city located in the State of Pará, northern of Brazil. For the training and construction of the Fuzzy Forecast Model, data from 71 projects were used and 16 others residential buildings were used for its validation. The results showed a significant level of assertiveness, with 75% accuracy considering a range, whose upper and lower limits were calculated from MAPE and MASE. The model presented a prediction performance superior to other models already consecrated in the literature. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
0.58 MB
- Informations
sur cette fiche - Reference-ID
10412515 - Publié(e) le:
12.02.2020 - Modifié(e) le:
02.06.2021